There is a current trend for telecommunications and data technologies are nowadays to merge into a single environment, largely due to cost aspects. The preferred technology seems employs asynchronous networks, probably mainly due to market penetration, rather than the fact that asynchronous networks offer a higher quality solution. One particular aspect of asynchronous networks which creates problems for telecommunication services is the lack of accurate clock transport.
There are a number of mathematical ways to solve the problem. Typical solutions used are based upon averaging, weighting, line fitting and combinations thereof. Still the final resolution remains limited due to a number of problems in the network. The nature of these problems is such that current models of networks and current implementations are not accurate enough to deal with the effect of time quantizers. Network models concentrate on probabilities and thus act as if the time base is continuous, which is not a correct assumption.
Various prior art solutions are described in, for example, U.S. Pat. No. 5,260,978, Fleisher et al., Synchronous residual time stamp for timing recovery in a broadband network; UK Patent App #: 0205350.2, Gordon J. Reesor, Clock synchronization over a packet network using SRTS without a common network clock; Fine Grained Network Time Synchronization using reference broadcasts, Jeremy Elson, Lewis Girod and Deborah Estrin, internet publication, mail addresses {jelson,girod,destrin}@cs.ucla.edu; Alignment of clock domains in packet networks, patent application, W. L. Repko et al.; Spectra of pulse rate frequency synthesizers, Venceslav F. Kroupa, app. In Direct Digital Frequency synthesis, IEEE, ISBN 0-7803-3438-8; and Oversampling Delta-Sigma Data Converters, Theory, Design and Simulation, James C. Candy, Gabor C. Temes, IEEE Press, ISBN 0-87942-285-8. The above documents are herein incorporated by reference in their entirety.
Clock alignment in packet networks requires the transport of a real time clock signal over a network. The goal in data networks, which is the main source for the emergence of asynchronous networks, is of course primarily to transport data, not time. The techniques used in asynchronous networks introduce time problems that typically appear as variable time delays. A common model of these delays assumes that they are pseudorandom. In fact the nature of the delays is more complex, and is built up of a number of error types and magnitudes.
Asynchronous networks are built up with elements that run on their own clocks. The clocks are typically generated with the help of crystals in order to provide reasonable stability. Digital circuits require cycle-to-cycle stability to guarantee setup and hold times. External interface clocks are derived from a crystal clock. This implies that the time quantization is defined by the crystal, which makes it also relatively stable for longer periods. If two of these clocks sample in series the effective difference of sampling frequencies can be relatively large, but it can also be quite small. The latter case leads to low frequency errors in the overall behaviour of the system.
Switches and routers have elements that can handle the statistical properties of traffic, for example queues. Such elements introduce delays, depending on other traffic passing through the switch/router, or internally generated traffic (typically management traffic). This delay is typically pseudo random, for it depends on other traffic streams that operate in their own environments.
Modern switches or routers have internal systems that sometimes rearrange the precise operation of the switch. For instance the priority of queue handling can be changed. This becomes even more apparent when the switching configuration becomes complex. Rerouting of traffic for instance implies relative large jumps in delay. Depending on precise operation the delay variation can either be very structured, for instance as a result of repetitive timed updating, or pseudo random, if it largely depends on other streams.
In the switch there may be processes with low frequency aspects, such as regular internal maintenance. Such internal operations may have some impact on the effective delays. This becomes much more complex if these delays appear at slightly different frequencies in subsequent nodes.
The appearance of a network of switches and terminators is a mixture of all of the above effects. When coarsely observed the queueing delays are dominant, which explains the standard approach with pseudo random models. When a closer look is taken it will appear that some regularity is present. A first level could be the effect of internal operations, and a finer level could be the quantizer level caused by the physical clocks in the elements. At the smallest level of detail the thermal noise will become apparent.
Next to the size of the delays, the different effects introduce their own typical problems. The queueing delays may be pseudo random in time, but are likely dominated with a few sizes that relate to the typical packet sizes. Thus the queueing delays may also carry a few typical frequencies of delay variation. More interesting are the structured elements. Delay variation due to internal management will be seen on relatively low frequencies, clock offsets can be on either very low frequencies (if the clock difference is small) or on much higher frequencies (for larger clock differences).
In order to get the best possible performance a clock recovery method should be able to deal with all these effects. Existing solutions concentrate on the coarse level, not on the finer levels, and provide solutions for his coarser level. Typically such solutions rely on the relative stability of local oscillators, compared to the behaviour of the network in-between. The knowledge of the stable local oscillators is a minimum requirement for decent suppression of the pseudo random effects. But when such a solution for those levels is available, the first next level of problems becomes apparent and dominant. Thus the quantizing level as introduced by the clocks in the network become dominant, for which the pure stability of the local oscillators at the end nodes does not provide a sufficient solution